The Impact of Fu’s Subcutaneous Needling on Lower Limb Muscle Stiffness in Knee Osteoarthritis Patients: Study Protocol for a Pilot Randomized Controlled Trial
Bibliographic record
Abstract
Hu Li,1,2,* Cong Cong Yang,3,* Tianyu Bai,1 Jian Sun,4,5 Zhonghua Fu,4,6 Jia Mi,3 Li-Wei Chou7– 9 1Department of Acupuncture-Moxibustion and Tuina, Shandong Provincial Third Hospital, Shandong University, Jinan, 250031, People’s Republic of China; 2School of Acupuncture and Tuina, Shandong University of Traditional Chinese Medicine, Jinan, 250355, People’s Republic of China; 3Department of Ultrasound, Shandong Provincial Third Hospital, Shandong University, Jinan, 250031, People’s Republic of China; 4Clinical Medical College of Acupuncture & Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, 510405, People’s Republic of China; 5Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, 510006, People’s Republic of China; 6Institute of Fu’s Subcutaneous Needling, Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China; 7Department of Physical Medicine and Rehabilitation, China Medical University Hospital, China Medical University, Taichung, 404332, Taiwan; 8Department of Physical Therapy and Graduate Institute of Rehabilitation Science, China Medical University, Taichung, 406040, Taiwan; 9Department of Physical Medicine and Rehabilitation, Asia University Hospital, Asia University, Taichung, 413505, Taiwan*These authors contributed equally to this workCorrespondence: Li-Wei Chou, Department of Physical Medicine and Rehabilitation, China Medical University Hospital, China Medical University, No. 2 Yuh-Der Road, Taichung, 404332, Taiwan, Email chouliwe@gmail.comBackground: Knee osteoarthritis (OA) is a leading cause of disability worldwide, with clinicians often observing increased muscle stiffness associated with joint pain and dysfunction. This study examines the impact of Fu’s Subcutaneous Needling (FSN), a non-pharmacological technique, on muscle stiffness in the lower limbs of individuals with knee OA.Materials and Methods: This study protocol is a pilot, single-center, randomized controlled trial. Sixty knee OA patients will be allocated equally for FSN or electroacupuncture (EA) treatments. Interventions will be applied thrice weekly for the first two weeks and twice weekly for the subsequent two weeks for a total of ten sessions. Assessments will be conducted at baseline, post-initial session, after four weeks of intervention, and at the end of a four-week follow-up. The primary outcome will be the muscle stiffness in the lower extremities, as measured by shear wave elastography (SWE). Secondary outcomes include response rate, a reduction in the mean pain intensity on the Numerical Rating Scale (NRS) by at least two points and on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) function subscale by six points at week four compared with baseline. Weekly monitoring of the NRS and WOMAC scores will determine the rapidity of pain alleviation and functional improvement, along with 12-item short-form (SF-12) score changes from baseline to week four.Results: This is the first standardized protocol examining the effects of FSN on lower limb muscle stiffness in patients with knee OA by SWE. We hypothesize that FSN could outperform EA in alleviating lower limb stiffness associated with knee OA. Findings will contribute to the body of knowledge regarding the efficacy of acupuncture-derived interventions in managing muscle stiffness and may guide future research directions.Study Registration: The trial has been registered on the Chinese Clinical Trial Registry (Registered number: ChiCTR2300073615). Registered 17 July 2023.Keywords: Fu’s subcutaneous needling, electroacupuncture, muscle stiffness, knee osteoarthritis, shear wave elastography
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".